阅读说明：本技术 数据处理的方法、训练神经网络模型的方法及设备 (Data processing method, method and equipment for training neural network model ) 是由 李成 于 2019-08-07 设计创作，主要内容包括：一种数据处理的方法,包括：获取多个待处理数据(501)；使用第一神经网络模型对多个待处理数据进行处理,得到与多个待处理数据一一对应的多个第一矢量(502),其中,第一神经网络模型是基于通用数据训练获得；获取第一关联关系信息(503),第一关联关系信息用于指示至少一个第一矢量组,每个第一矢量组包括满足先验假设的两个第一矢量；将多个第一矢量以及第一关联关系信息输入第二神经网络模型,得到针对第一待处理数据的处理结果(504),第一待处理数据是多个待处理数据中的任一数据。所述数据处理的方法的目的在于削弱神经网络模型对待训练数据的依赖性。(A method of data processing, comprising: acquiring a plurality of data to be processed (501); processing the data to be processed by using a first neural network model to obtain a plurality of first vectors (502) which are in one-to-one correspondence with the data to be processed, wherein the first neural network model is obtained based on general data training; acquiring first incidence relation information (503), wherein the first incidence relation information is used for indicating at least one first vector group, and each first vector group comprises two first vectors meeting the prior hypothesis; the plurality of first vectors and the first incidence relation information are input into a second neural network model, and a processing result (504) aiming at first data to be processed is obtained, wherein the first data to be processed is any one of the plurality of data to be processed. The method for processing the data aims to weaken the dependence of the neural network model on the data to be trained.)